genetics

Chickens are unlikely harbingers of the invention of time travel, but a recent study using a line of White Plymouth Rock foul developed in Virginia Tech’s College of Agriculture and Life Sciences caused evolutionary history to speed up a bit.

Specifically, the experiment proved that evolution happens 15 times faster than previously thought.

The research was published recently in Biology Letters, a journal of Royal Society Publishing. The discovery involved researchers from several universities, including the University of York, Oxford University, the University of Sydney, Uppsala University, the Swedish University of Agricultural Sciences, and Virginia Tech.

“This experiment and many others involving everything from animal appetites to genetics could never have been done without the pedigree lines here at Virginia Tech,” said Siegel, distinguished professor emeritus of animal and poultry sciences in the College of Agriculture and Life Sciences. “This experiment was also an excellent example of international collaboration between six countries that was necessary for the success of the study.”

Siegel’s other primary research area using genetic lines of chickens focuses on why some animals pack on pounds and others don’t, and will be a key component of finding out how to breed chickens to feed the projected 9 billion people set to besiege the planet in 2050.

The pedigree lines of White Plymouth Rock chickens were developed by Siegel, who began breeding them in 1957. From the common founder population, he produced two distinct lines of chickens selected for high- and low-body weight. Today, the high-weight line dwarfs its low-growth counterpart by an average of 12 times more by the time they reach the eight-week selection age.

In the latest experiment, researchers analyzed blood samples of chickens of the same generation using the most distantly related maternal lines to reconstruct how the mitochondrial DNA passed from mothers to daughters.

Mitochondria are specialized structures in the cells of animals, plants, and fungi that generate energy, synthesize proteins, and package proteins for transport to different parts of the cell and beyond.

Previously, estimates put the rate of change in a mitochondrial genome about 2 percent per million years,” Greger Larson, professor of archaeology at Oxford University, said in a news release. “At this pace we should not have been able to spot a single mutation in just 50 years, but in fact we spotted two.”

The sampling scheme yielded 385 mitochondrial transmissions that were analyzed for linkages within the mitochondrial DNA.

The rate of evolution was calculated by analyzing the number of observed mutations in the approximately 16,000 samples of mitochondrial DNA in the genome over 47 generations.

The scientists then reconstructed the maternal pedigree based on the mitogenome sequences.

“Our observations reveal that evolution is always moving quickly, but we tend not to see it because we typically measure it over longer time periods,” Larson said in the news release. “Our study shows that evolution can move much faster in the short term than we had believed from fossil-based estimates.”

The experiment also determined that mitochondria are not solely passed down from maternal lines. Strictly maternal inheritance has long been thought of as the characteristic of mitochondrial genomes.

“The thing everyone knew about mitochondria is that it is almost exclusively passed down the maternal line, but we identified chicks who inherited their mitochondria from their father,” said Michelle Alexander, lead author. This finding supports the theory that “paternal leakage” is not such a rare phenomenon.

Ok, so talking plants didn’t work out so well in “Little Shop of Horrors” when Audrey II started eating folks, but you don’t have anything to fear. Unless, of course, you are a tomato plant. Those guys need to be careful what the other plants are saying.

Professor Jim Westwood in the College of Agriculture and Life Sciences has recently discovered that plants use a sort of language to communicate with each other. Specifically, he found that when the parasitic plant dodder attacks tomato plants, there is a massive exchange of mRNA. It was thought that mRNA was very fragile and short-lived, so transferring it between species was unimaginable. The parasitic plants may be using this communication to exploit the host plants’ weaknesses.

“The discovery of this novel form of inter-organism communication shows that this is happening a lot more than any one has previously realized,” said Westwood, who is an affiliated researcher with the Fralin Life Science Institute. “Now that we have found that they are sharing all this information, the next question is, ‘What exactly are they telling each other?’.”

Science starts with a question. The research is not flashy, even with all of those glinting test tubes and fancy microscopes. It’s slow and specific. Answering that question takes years – sometimes even decades – and that’s just to gather information about one gene or one specific part of a mechanism that might be the solution. There’s no guarantee that the question will ever be answered.

The question is usually big: What causes cancer? Why does this gene mutate? When do neurons age? The path to a solution is usually narrow; it has to be, so how does any one ever choose what to focus on?

When rising fourth-year Virginia Tech Carilion School of Medicine student James Dittmar had to decide on a research project, he was overwhelmed with having to pick just one thing.

“How do you focus?” Dittmar asked. “How do you prioritize research?”

Dittmar explored a number of options with his mentor, Gregorio Valdez, an assistant professor at the Virginia Tech Carilion Research Institute, but none seemed quite right. It was in that exploration that Valdez was inspired to guide Dittmar into finding his ultimate project – helping others decide how to focus their own research. Thus, EvoCor was born.

EvoCor is a free search engine for genes. Type in a gene and EvoCor searches through thousands of mapped genes, different genomes, and larger datasets maintained by the National Institutes of Health. It pulls together a list of genes that evolved similarly. The genes are ranked by likelihood that they’re related functionally to the initial gene submitted.

Take a gene that is already well studied for a certain disease, like MUSK’s role in motor impairment in aging individuals. A scientist can type MUSK into EvoCor and EvoCor will return a list of possibly related genes that might work with MUSK to impair motor function as people grow older.

It’s not a slam-dunk, but it’s a far cry better than picking a random gene that may or may not be related at all. It’s a starting point.